IT Systems - Science topic

Moreover, you can consider IRS (INTELLIGENT REFLECTING SURFACES) and NOMA in LTE networks.

Dear Mr. Wijngaarden!

I found an article you might see as of value for your work:

Hrusto, A., Runeson, P. & Engström, E. Closing the Feedback Loop in DevOps Through Autonomous Monitors in Operations. SN COMPUT. SCI. 2, 447 (2021). https://doi.org/10.1007/s42979-021-00826-y, Open access:

An additional source of information might be the following article:

Oxfam GB (2022). HOW TO OPERATIONALISE ‘CLOSING THE FEEDBACK LOOP’: WHERE IS THE SOLUTION? Free access: https://www.elrha.org/project-blog/operationalise-closing-feedback-loop-isthe-solution/

Yours sincerely, Bulcsu Szekely

Big Data Analytics database and analytical technology can be helpful in the process of collecting and processing large sets of information and data on potential bank customers, including borrowers, enterprises being bank customers, data describing the economic and financial situation of enterprises and factors in their market, industry and competitive environment. etc. In this way, Big Data Analytics technology can be helpful in the context of improving the processes of analyzing the creditworthiness of potential borrowers and in terms of improving the credit risk management process.

Best regards,

Dariusz Prokopowicz

Inevitably. A more interesting question is to do what? And why?

1. Historically twisting have been designed to substitute a discontinuous controller with Lipschitz continuous one keeping the finite-time theretically exact convergence to the sliding output for the systems with relative degree one affected by Lipschitz perturbaitons(see Levant A. IJC, 1993 https://www.tau.ac.il/~levant/slorder93.pdf).

The only adavantage of the twisting controller is that if this algorithm is applied for the systems with relative degree two it ensures theoretically exact finite-time convergence of the sliding output and its derivative to zero in finite-time.

But from the viewpoint of chattering the twiating controller is the worst one because his gains are at least twice bigger, than the upper bound of uncertainties.

Moreover, the amplitude of chattering produced by twisting controller is bigger than the amplitude of chattering produced by relay controller with a linear sliding surface see attached file, table 3

Dear Professor Sabatier

First, I'd like to thank you so for asking these kind of challenging questions. These kinds of questions are very important for advancing this field. As you said, our life is full of doubts. Now this question arise that: How can we trust to different integer differential models? The only sin of fractional derivative is that it has been introduced after integer derivative. Why should we accept that the first derivative (u') denotes the velocity? Why another fractional derivative (such u^{0999}) is not?

As we can check in many considerable works, fractional derivatives modify many old results in integer derivatives. As you said, you often use fractional models to build and implement very physical and useful systems (eg: battery state observers, hydrogen generator, ...). We need a comparison in study of these different natural phenomena and so a standard basic theory for the comparison which is usually integer derivative models while we can doubt it. I fee that we could improve our initial mental attitude. Again, I appreciate you.

I'm trying to download pajek 5.10. e

Even though I had no problem dowloading PajekXXL, I'm not able to correctly download 32 nor 64 bit version of pajek 5.10

Corona is there because of the ionization around a charge carrying conductor. Since the negative terminal of a DC link carries negative charge, it repels the negative charge around the conductor reducing the chances of ionization and hence less corona is observed around it.

Dear Dr. Vineet Jain,

It is because of your program. Your definition in the program for train, validation, and test is wrong. You must find a mistake in your program. If you define train, validation and test true, the program does not return this "Warning" to you.

With best regard,

Zahra Pezeshki

If you are referring to cross-over frequencies, your statement is true in a specific case. If you have a system such that the Amplitude ratio is a monotonically decreasing function of frequency, then if your gain cross-over frequency is smaller than phase cross-over frequency, your system will be stable. However, it is not true in general.

Have anyone of you have worked on Inducible Pan-Endothelial Cre/ERT2 Mouse Model? Could you give me any suggestions?

If I would be "simple", since your refer a need to model "innformatics sytèms", I would suggest to you to consider the set of "languages" that are being standerdized by the Object Management Group (https://www.omg.org/). There you will find "solutions" such as UML, BPML/N...

Nevertheless, keep in mind that currently, these solutions are mostly applied by IT people.

And fare less in the business or in the area of technical people (other than IT).

As a matter of fact, there are various languages and tools to adress yours expectations.

And I have to say also that they are more or less relevant, in terms of "acceptance" notably, depending on the context they are applied. This comes to the fact that there are different "modelling communities", each having its languages and related tools.

So, you should take this context into consideration. And being ready to apply or adapt yourself to different languages and tools, depending on the context you interact with, at some points.

One thing is "syntactically agnostic" : the "ontology" "behind" the modelling languages.

And this is the mastering or, simpler, the sense of such an ontology that allow to "translate" syntactics formalisms from each to the others.

To complete this question, How can i find the coordinates of two points in triangle with one coordinate and lengths known in 2 Dimensional system?

Entropy: A concept that is not a physical quantity

What is the major differences between "master slave", "peer to peer"?(difference in cost communication)

In my view, and in the views of many developers and customers, OTRS is the best one.

it's may help

Thanks for the reply Yin. However, it does not answer my question.

You can get some ideas (and a not bad working implementation) here http://www-lium.univ-lemans.fr/diarization/doku.php/quick_start

Thank you professor Leyvraz for taking the pain to write an excellent answer. I appreciate it very much. It was nice to hear from you. When I was working on aggregation I read your articles a lot. Reading a paper is like learning the author. Your papers helped a lot in pursuing my research. Indeed, the difference between first and second order phase transition is quite tricky. I am now looking at other parameters as well. Take care.

Hello Prof. Kamberaj , Thanks a lot  for your answer. But unfortunately I can't calculate the free energy of system. Your suggestion is highly appreciated. All the best.

The system of linear equations has unique solution. Please see the attachment.

Your question was how can one improve the resolution. The limit if of course diffraction. However, there are some practical ways to improve resolution. First, I'd recommend using focusing mirrors instead of lenses whenever possible. Off-axis paraboloids are conic sections and show no spherical aberrations when focusing an incident plane wave. Use two of them for a confocal imaging system. Even better, if you can measure amplitude and phase, then you don't even need a mirror, but the knowledge of phase and amplitude in the diffraction pattern will allow you to reconstruct the object, much like it is done in holography. The problem here may be signal to noise for time domain systems. I also suggest you set up your system with a visible light source. If it looks good for visible light, it will look good for THz.   

The fundamental problem with many THz imaging systems is that we use fairly small optics to get the job done, often with unsatisfactory results. Remember, THz wavelengths are 1000 times longer than visible wavelenghts, but we don't have 1000 times larger optics of course. Still, go big, like 5 inch mirrors, or even larger. This can become costly if you make such a mirror at visible light quality, but you don't have to. You can save a lot of money by relaxing the tolerances to THz wavelength quality. 

Lastly, coherence can be a problem in the form of stray light, multi-path, etc. Make sure you take that into account when setting up your imaging system. 

Many Commercial off the shelf [COTS] ERP solutions are available for example SAP, Oracle, Microsoft...which cater from very large to small businesses, from simple to very complex business processes, You can save time in "re-inventing the wheel" by using any of these "ready to use: solutions.

Careful design of the low-pass filter in conjunction of the PWM sheme used, switching frequency etc. Refer to this paper, which refers to a lot of work I covered in my PhD thesis on this issue:

Dear Yacine ,

The following thesis aims to bridge the gap that exists between the concepts and technologies which are normally used to test message-based discrete systems and those which are used to test hybrid and continuous systems. The combination of hybrid and continuous systems is especially unique and will be relevant in the testing of future systems that are conceptually continuous or hybrid and make extensive use of message-based communication in their interactions with other systems.

You can download a generic m-file in order to calculate the B-loss coefficients of any systems, you must have in your path matpower, in the following link:

I can give u some advises if still not achieved the work...

Dear Edwin,

I suggest for you a links and attached files in topics.

-IEEE Xplore - Conference Table of Contents

ieeexplore.ieee.org/xpl/topAccessedArticles.jsp?punumber... -

-An improved particle swarm optimization for exponential stabilization ...

-chaotic lorenz system: Topics by WorldWideScience.org

-unified chaotic systems: Topics by WorldWideScience.org

-Computer Science Seminars - de l'Université libre de Bruxelles

Best regards

Look at this doc it may be helpful for your topic. Good luck.

Wait, the volume control and the tuning control in any ancient tube radio are already examples of "programmable analogue systems." And too, jumpers used in analogue circuit boards, to select certain functions or adjust certain features.

I think that programmability of digital vs analogue becomes ultimately a matter of degree. We used to have an analogue computer lab back in my undergrad days. They also were programmable. They consisted of banks of opamps. Programming was done by plugging individual component modules onto a board, to establish input, output, and feedback circuits for the opams, and then plugging that board onto the front of the computer. Used mainly to solve differential equations.

Somewhat like this:

 Can you use beryllium fluoride or beryllium oxide?

Hello Muhammad Shafiq 

 Internet of Things (IoT)

Devices, computers, and machines were already connected by the time Kevin Ashton coined the term Internet of Things. The concept gained steam for its ability to connect the unconnected – physical-first objects previously incapable of generating, transmitting and receiving data unless augmented or manipulated. Embedding sensors, control systems, and processors into these objects enables horizontal communication across a multi-node, open network of physical-first objects.

The term is also vaguely used to describe connected digital-first devices such as wearable gadgets that may be classified as Internet of Digital while offering the same functionality as its physical-first counterpart developed into a smart connected technology. The meaning and application of the term IoT will continue to evolve as new connected technologies emerge, replacing physical-first objects with smart connected devices and use-cases to constitute all new “Internet-of-X” classifications. Examples of IoT includeconnected cars, smart meters, and smart cities, among others.

The Internet of things (stylised Internet of Things or IoT) is the internetworking of physical devices, vehicles (also referred to as "connected devices" and "smart devices"), buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data. In 2013 the Global Standards Initiative on Internet of Things (IoT-GSI) defined the IoT as "the infrastructure of the information society.The IoT allows objects to be sensed and/or controlled remotely across existing network infrastructure, creating opportunities for more direct integration of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit.When IoT is augmented with sensors and actuators, the technology becomes an instance of the more general class of cyber-physical systems, which also encompasses technologies such as smart grids, smart homes, intelligent transportation and smart cities. Each thing is uniquely identifiable through its embedded computing system but is able to interoperate within the existing Internet infrastructure. Experts estimate that the IoT will consist of almost 50 billion objects by 2020.

Typically, IoT is expected to offer advanced connectivity of devices, systems, and services that goes beyond machine-to-machine (M2M) communications and covers a variety of protocols, domains, and applications. The interconnection of these embedded devices (including smart objects), is expected to usher in automation in nearly all fields, while also enabling advanced applications like a smart grid, and expanding to the areas such as smart cities.

"Things," in the IoT sense, can refer to a wide variety of devices such as heart monitoring implants, biochip transponders on farm animals, electric clams in coastal waters,automobiles with built-in sensors, DNA analysis devices for environmental/food/pathogen monitoring or field operation devices that assist firefighters in search and rescue operations. Legal scholars suggest to look at "Things" as an "inextricable mixture of hardware, software, data and service".These devices collect useful data with the help of various existing technologies and then autonomously flow the data between other devices. Current market examples include home automation (also known as smart home devices) such as the control and automation of lighting, heating (like smart thermostat), ventilation, air conditioning (HVAC) systems, and appliances such as washer/dryers, robotic vacuums, air purifiers, ovens or refrigerators/freezers that use Wi-Fi for remote monitoring.

As well as the expansion of Internet-connected automation into a plethora of new application areas, IoT is also expected to generate large amounts of data from diverse locations, with the consequent necessity for quick aggregation of the data, and an increase in the need to index, store, and process such data more effectively. IoT is one of the platforms of today's Smart City, and Smart Energy Management System

The term “Internet of Things” coined by British entrepreneur Kevin Ashton in 1999 described connectivity among physical objects and no longer holds in its original form. It is now largely overlapped, confused and even mystified with the term Internet of Everything (IoE). IoE is considered a superset of IoT and Machine-to-Machine (M2M) communication considered a subset of IoT. Let’s take a closer look into differences between IoT, IoE, and M2M, which has impacted consumers and businesses alike.

Although the concept of Internet of Everything emerged as a natural development of the IoT movement and is largely associated with Cisco’s tactics to initiate a new marketing domain, IoE encompasses the wider concept of connectivity from the perspective of modern connectivity technology use-cases. IoE comprises of four key elements including all sorts of connections imaginable:

People: Considered as end-nodes connected across the internet to share information and activities. Examples include social networks, health and fitness sensors, among others.

Things: Physical sensors, devices, actuators and other items generating data or receiving information from other sources. Examples include smart thermostats and gadgets.

Data: Raw data analyzed and processed into useful information to enable intelligent decisions and control mechanisms. Examples include temperature logs converted into an average number of high-temperature hours per day to evaluate room cooling requirements.

Processes: Leveraging connectivity among data, things and people to add value. Examples include the use of smart fitness devices and social networks to advertise relevant healthcare offerings to prospective customers.

IoE establishes an end-to-end ecosystem of connectivity including technologies, processes and concepts employed across all connectivity use-cases. Any further classifications – such as Internet of Humans, Internet of Digital, Industrial Internet of Things, communication technologies and the Internet itself – will eventually constitute a subset of IoE if not considered as such already.

A cyber-physical system (CPS) is a mechanism controlled or monitored by computer-based algorithms, tightly integrated with internet and its users.

Rodolfo:

En mi ultimo libro del año pasado sobre regímenes deslizantes se trata el caso de superficies variantes en el tiempo.

No hay ninguna dificultad especial porque los sistemas sean variantes en el tiempo y se quiera imponer una condición algebraica cuya variedad de nivel cero sea invariante en el tiempo.

s=h(x)

\dot x = f(x,t)+g(x,t)u

\dot s = < dh, f(x,t)+g(x,t)u>

las condiciones de invarianza  s= 0, ds/dt=0

definen el control equivalente  u = -<dh,f>/<dh,g>

la condición necesaria para que exista régimen deslizante es que uniformemente

en el tiempo <dh,g(x,t)>\not=0. (transversalidad homogénea en el tiempo)

etc. etc.

I'am looking for a CDR structure for a Nokia's MSS system working on software M15 version too. Is there so easy to get the name of those storage to go there and then download it? Please I would like to know those? Regards 

check addgene page

One can attach nitogen cylinder(s) to the closed system. This is the only way to induce hypoxia. The system works well and maintains the hypoxia at the desirable level.

Hello,

I am not sure what question you came across, but I wish you to refer to one of my papers as follows. Wish it helps you.

Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Aug;72(2 Pt 1):021902

Signal-to-noise ratio gain of a noisy neuron that transmits subthreshold periodic spike trains.

Good luck

Yanmei

Dear Sir,

pl study this US patent.

all the best

Dear Anouncia,

The following link is related with the interested thesis, and may be useful for your work:

Dear Anulekha

I think you are working on optimal power flow.  Please find herein attached file where you can get the data set with limits and generator cost coefficients of 15 generators. I hope you will find it useful for your work. Good luck.

Prof. Ian, exactly that what I meant

We can say the system is hyper-chaotic system because the LEs are +, +, 0, -.

There is no requirement related to the large Lyapunov exponent.

System is meant to be much more sensitive to initial conditions for higher Lyapunov exponent.

Dear Maurya Gyanprakash 

If you are looking for the constants and the variables you need to reformulate the problem as:-

k1= a1*x^2+b1*x*y+c1*z=d1

k2= a2*x+b2*x*y^2+c2*z*x=d2

k3= a3*x+b3*x*y+c3*z=d3;

Thus the objective function becomes:-

f= k1+ k2 + k3 -d1-d2-d3

the Optimizer will change both the constants and the variables to reach the value of f to zero

Good luck

Prof. S. EL-Rabaie

I agree with the above but the interaction has to be inviting and user friendly like wise for the instructional system if you do not have a user interface the instruction become boring and people loose interest. The average attention span of a person is 15 minutes, and you only have the first 5 minutes of interest, that is how long it will take a regular person to process and decide

Dear Majid,

I think there is no difference in the method of calculating the bit error rate in both cases.

The difference only is that one substitute the spreading sequence by a chaotic sequence. In both cases one get the spread signal which is binary phase keyed and sent across white additive Guassian noise channel.

So in this case the chips may be detected in errors because of the additive noise. 

Then one correlates the received spreading signal with the spreading sequence irrespective of its type. After despreading one gets an estimate of the input data sequence. When compared to the input sequence one gets the bits in error and the bit error rate.

In summary one uses the same same signal processes to get the bit error rate.

wish you success

Dear;

As you know, in the transmitter of OFDM system, to transmit the frequency components of the OFDM symbol, the signal must be represented in the time domain. This is accomplished by the IFFT. so you can not replace IFFT by FFT  theoretically and analytically.

In our society, the family-school partnerships are very important for supporting students in different ways. For example, many parents send students to "extra lessons" after school in order for them to pass for a prestige school for the Secondary Entrance Assessment. I hope this helps.

Best regards,

Debra

https://msdn.microsoft.com/en-us/library/dd239405.aspx 

You can check out this link, you might find it useful 

Well, given it's a matter of money, not of time: building the measurement equipment on your own might be worth some bachelor's/master's theses. Maybe you'll find 'sponsors' regarding the potential improvent in power supply quality...

Wish you success

Lots of thanks. It was helpful.

Best wishes.

This is the paper I presented in PIDE, Islamabad in 2014.

Dear Ishan,

I would like to suggest you to take a look in the articles in the links below. The second one proposes a data structure that did not require any verification of the radiality. The first one is the first articles that applied this data structure in problems that involve

network reconfigurations.

Beste regards.

Dear Walid,

Thank you for raising this important question. Both CPS and IoT are holistic visions for the outlook for computing and communication in tomorrow's world. They come from different research communities, though, and so they have different emphasis. CPS has roots in control, computer science, real-time systems, and sensor networks. IoT has roots in communication networks and wireless communication. This tends to influence the focus of research in conferences that highlight the particular topic. CPS emphasizes hybrids systems and formal verfication of dynamical systems. IoT emphasizes communication protocols. Both also consider issues of privacy and security, among many others.

This description is for the research areas under those names. When one says CPS, it is best to consult Lee and Seshia for origins of the term (due to Helen Gill). IoT is a more general term and I am not aware of a standard reference for it.

Personally, I think it would be very good if the two communities interact more, since the future is likely tobe shaped by work in both.

Kind regards,

Walid.

Hello Dear Nour Moustafa

If you know the number of features

Give a weight to each feature

Have you tried to use gnuplot? It's runs in Linux and windows systems.

Please, check this link:

Substituting x(t) = bexp(at) gives the equation for a:

a = A + A1 exp(-aT)

Solve it. Initial condition gives b.

It depends on your interest. 

If you check the stability of the f/b interconnection of only two systems, then it is just a sufficient condition. If you check the stability of the f/b interconnection between one system $G$ and all the systems with Hinfty norm smaller $1/|G|$ then it becomes "if and only if". 

Loosely speaking, if you go to a book of nonlinear control e.g. Vidyasagar, Khalil, etc, you will find the "if" condition. If you read a book about H_infty, e.g. ZDG, then you will find the "if and only if".

a context-aware recommender system is considered the hottest area in the recommender system. It 's not like traditional one depends only on item and user entities,it considers any contextual information, such as time, place and etc. It is also important to bring the contextual information into the recommendation process in order to recommend items to users under certain circumstances. for example in the online  restaurant, if you log in the page in the morning , the recommender system will suggest a breakfast meal based on your preferences. The same thing happens when you log in at evening , the recommender system will suggest a dinner meal.

you can check the book

Recommender Systems Handbook, chapter 7, by Francesco Ricci et al.

It gives examples of applications in context-aware recommender systems.

What is exactly the CCA system? Can you please attach reference articles or any link pointing to the source. Thanks.

In my mind, the incomplete h-cube architecture works meant to exploit the cube as component may fail and the structure loses its perfect cube nature (so one design algorithms overcoming the structure failures during repair time; one does not want local failure to make the entire architecture down!!)

Find a theoretical scheme, in the attached document, for gyro-less inertial navigation system (using accelerometer only)

"Flush port" on the Agilent 1200-series (Well plate sampler waste valve or Prime purge valve?). Are you referring to the Prime Purge valve located on the pump head? If so, this valve should be opened each time you wish to change mobile phase solution; change bottles or manually purge the system of bubbles or liquid. Normal position is closed. We normally open this valve at the start of each day to wash mobile phase from all of the channels (one at a time) through the system to waste to remove gas which has bleed into the system when not in use. Note: This is a very delicate needle valve and should be opened one or two turns at most, using your fingers (not a wrench). Turn counter-clockwise to Open. Turn clockwise to close and just snug it closed, do not turn the valve so hard that you have trouble opening it again. You will damage it. You can check to confirm it is closed by looking for liquid to exit through the waste tubing connected to it. When closed, no liquid should come out of that line.

Carry Over: If your instrument has been properly maintained (a worn injector rotor seal will cause sample carry-over), then you should not have any issues with sample carry over with an Agilent 1200-Series Autosampler at all. They utilize a needle/pump flow through design so carry over is not possible 99.9% of the time. The entire flow path from needle, needle seat, loop, injector pump to column is continuously washed (not true of other HPLCs) so any left over material is continuously flushed out during your method. The outside of the needle is the only area left "unwashed", but this is rarely and issue, and if needed, a dip (described later) can help. This fantastic autoinjector design works great, but does increase system volume (we can discus how to improve that aspect later on, if needed). The most significant way you can induce carryover in this type of system is to not understand how it works and use the wash vial. Do not use the wash vial feature. It is not needed, except under rare circumstances. Do not program the injector to do anything but inject the sample as designed. We often see chromatographers who have no experience or formal training using HP or Agilent HPLC systems have carry over issues with these modules because they are so used to having these problems with other brands of systems (esp Waters). They have not received proper training in how to use these A/S with their different designs, so make things worse by using a wash vial. By learning how they work, you can make better decisions how to use them. ;)

If you would like to read more about how to troubleshoot and reduce sample carryover (carry-over) in HPLC and LC-MS systems for this and many other HPLC brands, please read the attached article link, "Carry-Over (Carryover) Contamination in HPLC and LC-MS Systems ". *The information contained within it has been taught by my to thousands of scientists over the years as part of fundamental chromatography training and service classes.  I think it will answer most of your questions.

Shannon's equation relates the capacity of a channel, C (in bits/sec), to the bandwidth of that channel in Hz and the signal to noise ratio. (Note: that S/N is a power ratio, not in dB but the actual ratio. Also note, that logarithm is base 2 log, not base 10 or natural log.)

Now, this equation would quantify how much noise a jammer would need to introduce into the frequency channel, to disrupt communications. As long as the jammer knows how wide the RF channel is, and how much capacity the users are trying to get from that channel, a jammer can decide where to locate his device and how much noise power to introduce. The goal is, of course, to reduce the SNR at either end of the comms  channel enough to prevent communications from occurring.

The users can counter by reducing their capacity requirement (such as simplifying the QAM constellation), increasing power, changing their RF channel, or moving further away from the jamming device. Or a combination of these steps.

One thing to keep in mind is that the noise assumed in the equation is Gaussian noise, white noise. There are potentially other ways of jamming a signal, such as to create reflections of the symbols or other such tricks, where clearly Shannon's equation by itself might not be enough to describe what's going on or how to protect oneself.

In throughput you need to measure the packets passed through link(s) in unit amount of time. It does not half much relation w.r.t. full duplex or half dulpex channel 

Dear Irene:

Thank you very much for your answer, agree that the importance of the evalauicón is what you learn.

Greetings, Mercedes

the crystalmaker design depend on its dihedral (symmetric)group.  

Get the state space model of the system. Then  use the MATLAB commnd eig(A).

When you take an incompressible fluid in a pipe with samll diameter d_s and another pipe with large diameter d_l. The viscosity should be the same in both systems (same fluid). Then you will observe that in both cases turbulence sets in at about Re=2300. This requires a higher velocity at smaller radius. But you must be aware that we talk about the diameter averaged mean velocity.

Two different systems (e.g. different size) will deliver the same answer when they show the same Re number. The art is to define the adequate characteristic length of the system when the geometry is getting more complex.

The concept of the Re number is also useful to trasnlate the result not only from one pipe system to another but also to do measurements in oe fluid and to translate the result to another one. Same behaviour at same Re number.

Best wishes.

The cost is often some function of the reciprocal of link speed. Cost is pretty much whatever the network designer wants it to be, to "encourage" the use of certain links, and "discourage" the use of alternate, or fallback links.

Since you mention routing specifically, we're talking layer 3. At layer 3, the path cost can possibly include the speed of the layer 2 network between the two adjacent routers, perhaps the distance of that layer 2 network, or perhaps the layer 3 network owner prefers to keep messages flowing through his own layer 2 nets, and wants to discourage use of outside layer 2 nets, so he artificially reduces the cost of his own infrastructure.

An early look at these questions would be Ford and Fulkerson's "Flows in Networks" (ISBN 0-691-07962-5). The "networks" can be anything, not just electronic communications. So path costs are whatever makes sense for the individual problem.

To answer to your question, I would like to illustrate my explanation with the figure attached below. It corresponds to the probability density functions associated with both hypothesis (H1: signal present, H0: signal abscent). I am assuming that the signal of interest is a baseband signal (e.g. pulses, PWM, PPM, etc.), and that the noise is Gaussian and zero-mean.

Let gamma be the threshold for discriminating between H1 and H0. Then the probability of detection (Pd) is the area under f1(x) at the right-side of gamma. On the other hand, the probability of false alarm (Pfa) is equal to the area under f0(x) at the right-side of gamma.

The ROC curves are plots of Pd vs. Pfa. There will be different ROC curves for different SNRs (signal to noise ratio). If the noise variance is constant, and a change in SNR is only due to a change in the pulses amplitudes, then an increase of SNR means that f1(x) will "move" to the right (the mean will be increased). Thus, the gray area (Pfa) in the figure will remain the same, but the area under f1(x) at the right-side of gamma (Pd) will be increased. And viceversa: if the SNR is decreased, then the Pd will be decreased.

Anyway, the Pfa doesn't change, and the Pd is strictly related with the SNR.

That is why two different ROC curves (associated to differents SNRs) will never cross each other, because for every Pfa, different Pd values will be obtained for a different SNR values.

I hope I have explained it well.

Best regards,

LM Gato.

With the help of a semantic net two things

can be done. The first is simple: expand

the query by adding synonyms. Applicable

in the case the search engine is able to

ignore extra keywords. Google can do that.

A problem arises if there are really much

words associated with a search keyword

entered. In this case a moderate percolation

should take place. Suppose the semantic

neighbors of a keyword w form several

cliques. Then you could pick 1 item of

each clique, for example the one that

has the greatest semantic distance in

terms of random walk visits from w.

Another thing that can be done with

the help of a semantic network

allows for adding boolean operators

to a query. Suppose someone enters

dog puppy dwelling hut.

With the help of a semantic network,

which can provide info about semantic

distance, it can be seen that dog and

puppy are semantically close to each

other, like dwelling and hut. It is

reasonable to insert 'or' operators

between keywords that mean similar,

and to insert 'and' operators between

semantically different terms. In this

case the query could be changed to

(dog or puppy) and (dwelling or hut).

It should also be mentioned that instead

of using boolean ands and ors the

fuzzy logic could be applied. Fuzzy logic

demands truth values between 0 and 1.

A semantic network can provide that by

mapping the semantic distance to the

interval 0..1, meaning low or high

semantic distance.

Regards,

Joachim

With the continually increasing pressure on organizations to secure and protect data, DFD has never been more important.  Effective - and auditable - data stewardship are essential.  One must be able to demonstrate how data is being collected, where it goes, where it's stored, who has access to it (and for what purpose), and how/when it is destroyed.  The simplest way to trace the data life cycle is through a higher level tool such as a DFD where the focus is on the data rather than on presentation and processing. 

unfortunately there is no general solution, the details of expected deployment system are essential in the next steps of solution design

Most of the approaches for PAPR reduction in OFDM systems should takes into consideration of also minimization of the Side-lobes at the same time. I enclose for you some useful papers applied for the cognitive Radio concerns this topic.